Pramod Gupta - Böcker

World population is increasing at an alarming rate and this has resulted in increasing tremendously the demand for tree products such as wood for construction materials, fuel and paper, fruits, oils and medicines etc. This has put immense pressure on the world’s supplies of trees and raw material to industry and will continue to do so as long as human population continues to grow. Also, the quality of human diet, especially nutritional components, is adversely affected due to limited genetic improvement of most of fruit trees. Thus there is an immediate need to increase productivity of trees. Improvement has been made through conventional breeding methods, however, conventional breeding is very slow due to long life cycle of trees. A basic strategy in tree improvement is to capture genetic gain through clonal propagation. Clonal propagation via organogenesis is being used for the production of selected elite individual trees. However, the methods are labour intensive, costly, and produce low volumes. Genetic gain can now be captured through somatic embryogenesis. Formation of embryos from somatic cells by a process resembling zygotic embryogenesis is one of the most important features of plants. In 1958, Reinert in Germany and Steward in USA independently reported somatic embryogenesis in carrot cultures. Since then, tremendous progress in somatic embryogenesis of woody and non-woody plants has taken place. It offers a potentially large-scale propagation system for superior clones.

World population is increasing at an alarming rate and this has resulted in increasing tremendously the demand for tree products such as wood for construction materials, fuel and paper, fruits, oils and medicines etc.

This includes mathematical operations with array data structures, Data Manipulation, Data Cleaning, machine learning, Data pipeline, probability density functions, interpolation, visualization, and other high-performance benefits using the core scientific packages NumPy, Pandas, SciPy, Sklearn/Scikit learn and Matplotlib.

This includes mathematical operations with array data structures, Data Manipulation, Data Cleaning, machine learning, Data pipeline, probability density functions, interpolation, visualization, and other high-performance benefits using the core scientific packages NumPy, Pandas, SciPy, Sklearn/Scikit learn and Matplotlib.

This book provides an introduction to machine learning, security and cloud computing, from a conceptual level, along with their usage with underlying infrastructure.

This book provides an introduction to machine learning, security and cloud computing, from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and best practices for using AI and ML in a dynamic infrastructure with cloud computing and high security, preparing readers to select and make use of appropriate techniques. Important topics are demonstrated using real applications and case studies.

Unlock the future of healthcare innovation with this comprehensive guide to AI and machine learning in medical software. Designed for engineers, data scientists, and healthcare leaders, this book provides a practical roadmap for developing safe, effective, and compliant AI/ML-driven medical devices. From foundational principles to advanced deployment, including Software in Medical Devices (SiMD) and Software as a Medical Device (SaMD), this book covers everything you need to know. Explore a unique end-to-end development methodology tailored for AI-enabled solutions, cloud architectures, and regulated healthcare environments. Discover how to streamline product releases, navigate privacy and security mandates, and master global medical device regulations—all this while accelerating time to market with real-world strategies and tools. Hands-on projects and exclusive case studies, such as Apple’s Sleep Apnea Notification and Notal Vision’s Home OCT system, provide actionable insights from the cutting edge of AI-powered diagnosis and care. Whether you’re just starting or scaling enterprise-grade AI, this book teaches you how to leverage tomorrow’s innovations, including Generative AI, federated learning, edge deployment, and cloud-native best practices. Keep usability, trust, and safety at the heart of your solutions. This book bridges the technical and clinical worlds, making it your indispensable companion for building the future of intelligent healthcare.Unique Selling points: Describes each stage of AI/ML-enabled medical device development, covering both regulatory and technical requirements;Illustrates how AI/ML-enabled device development differs from traditional software development in medical devices;Includes strategies for addressing common challenges during development and regulatory review.

World population is increasing at an alarming rate and this has resulted in increasing tremendously the demand for tree products such as wood for construction materials, fuel and paper, fruits, oils and medicines etc.